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Technology Portfolio Planning and Management : Practical Concepts and Tools - Oliver Yu

Technology Portfolio Planning and Management

Practical Concepts and Tools

By: Oliver Yu

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Published: 18th December 2006
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From the large overall scope of planning and management of technology, Technology Portfolio Planning and Management: Practical Concepts and Tools will focus specifically on the concepts and tools for the planning and management of an investment portfolio by a government or a business organization for either the development or the application of technologies. A portfolio is a coordinated combination of technologies that achieve a common objective for the decision-maker. Thus, the book will focus on those concepts and tools for selecting and modifying such a combination of technologies that will be either developed by a technology supply organization, such as a national laboratory or a corporate research center, or adopted by a technology application organization, such as a government administrative office or a corporation management department, to either advance public goals (such as space exploration or disease eradication) or enhance corporate strategies (such as improving productivity or increasing competitiveness).

In addition, many concepts and tools to be discussed in this book are well-established technical disciplines of their own: Analytic Hierarchy Process, Expected Utility Theory, Time Series Forecasting, Scenario Planning, Linear Programming, Dynamic Programming, Decision Tree Analysis, Real Options Theory, and Project Evaluation and Review Technique. The purpose of this book is to utilize the basic principles and practical applications aspects of these concepts and tools that are particularly relevant to technology portfolio planning and management.

Prefacep. v
Table of Contentsp. vii
Introduction and Overviewp. 1
General Scope of Planning and Management of Technology Development and/or Applicationp. 1
Focus, Purpose, and Emphasis of This Bookp. 2
Technology Portfolio Planning and Management Decision Frameworkp. 3
Complexity of Technology Portfolio Planning and Management Decisionsp. 5
The Role of Analysis and a Proper Balancep. 7
Organization of the Bookp. 9
Quantify Values and Risk Attitudesp. 9
Create Innovative Alternativesp. 9
Determine and Forecast Relationships-Major Analytic Methodsp. 9
Determine and Forecast Relationships-Qualitative Approachesp. 9
Search for Optimal Choice-Deterministic Approachesp. 9
Search for the Optimal Choice-Decision Under Uncertaintyp. 10
Monitor Portfolio Progress and Environmental Changesp. 10
Modify Portfolio to Reintegrate with Organizational Strategyp. 10
Appendixp. 11
Referencesp. 11
Exercisesp. 11
Quantify Values and Risk Attitudesp. 13
Simultaneous Rating Approachp. 13
Analytic Hierarchy Processp. 14
Set up the Hierarchy of Valuesp. 15
Set up a Standard Scale for the Pair-wise Comparisonp. 16
Develop an nxn Pair-wise Comparison Matrix for the n Values in a Hierarchyp. 16
Estimate the Average Preferences or Weights of the n Values in a Hierarchyp. 17
Check Matrix Consistencyp. 17
Revise the pair-wise comparison matrix for consistencyp. 18
Distribute the Relative Preference of a Value to Values in a Sub-hierarchyp. 19
Utility Theory Approachp. 20
Completeness and Rankabilityp. 21
Transitivity and Consistencyp. 21
Substitutabilityp. 21
Computability of Expected Utilityp. 21
Continuity of Expected Utilityp. 22
Utility of Monetary Valuep. 22
Utility of an Intangible Valuep. 22
Utility of a Candidate Technologyp. 23
Risk Attitude and Risk Premiump. 23
Equivalence and Reconciliation between the Analytic Hierarchy Process and the Utility Theory Approachp. 27
Referencesp. 28
Analytic Hierarchy Processp. 28
Utility Theoryp. 28
Exercisesp. 29
Create Innovative Portfolio Alternativesp. 31
Productive Brainstormingp. 31
Lateral Thinkingp. 32
Theory of Inventive Problem Solving (TRIZ)p. 33
Principle of contradictionp. 34
Principle of idealityp. 34
Principle of root cause analysisp. 34
Principle of related solutionsp. 35
Principle of unrelated combinationsp. 35
Principle of technology evolutionp. 35
Referencesp. 36
Generalp. 36
Brainstormingp. 36
Lateral Thinkingp. 36
TRIZp. 36
Exercisesp. 36
Determine and Forecast Relationships: Major Analytic Methodsp. 39
Develop Simplified Near-Term Relationshipsp. 39
Aggregate approachp. 39
Proportionality approachp. 40
S-shaped curve approachp. 40
Forecast Future Technology Capability, Demand Growth, and Market Penetrationp. 42
Underlying assumption 4A: future follows a historical patternp. 42
Underlying assumption 4B: future is analogous to a well-known phenomenonp. 49
Underlying assumption 4C: future can be assessed from a causal relationship-based large-scale system modelp. 52
Referencesp. 52
Exercisesp. 53
Determine and Forecast Relationships: Qualitative Approachesp. 55
Underlying Assumption 5A: Understanding the Future Through the Power of Expert Opinion or Collective Wisdomp. 55
Delphi methodsp. 55
Consensus approachp. 56
Major advantages, pitfalls, and applicabilityp. 56
Underlying Assumption 5B: Understanding the Future Through the Guidance of Leading Indicatorsp. 56
Patent and citation analysisp. 57
Survey of technology early adoptersp. 57
Major advantages, pitfalls, and applicabilityp. 57
Underlying Assumption 5C: Understanding the Future Through Reasoned Analysisp. 57
Cross-impact matrixp. 57
Hierarchical influence tracing systemp. 58
Analytic hierarchy processp. 59
Major advantages, pitfalls, and applicabilityp. 60
An Alternative Integrated Approach: Understanding the Future Through Decision-Focused Scenario Analysisp. 60
Basic characteristicsp. 61
Scenario development processp. 62
Resource requirementsp. 63
A real-world applicationp. 64
Insights, caveats, and recent advancesp. 70
Major advantages, pitfalls, and applicabilityp. 71
Referencesp. 71
Delphi Methodp. 71
Cross Impact Analysisp. 71
Hierarchical Influence Tracing Systemp. 72
Analytic Hierarchy Processp. 72
Scenario Analysisp. 72
Exercisesp. 72
Find the Optimal Technology Portfolio: Major Deterministic Methodsp. 75
Aggregate Approach 1: Benefit-Cost Ratio Methodp. 75
Algorithmp. 76
Illustrative examplep. 76
Major advantages and disadvantagesp. 76
Aggregate Approach 2: Multiple Rating Evaluationp. 77
Algorithmp. 77
Illustrative examplep. 78
Major advantages and disadvantagesp. 78
Aggregate Approach 3: Analytic Hierarchy Processp. 79
Algorithmp. 79
Illustrative examplep. 80
Major advantages and disadvantagesp. 81
Increasing and Concave Value Function: Generalized LaGrange Multiplier Methodp. 81
Mathematical foundationp. 82
Algorithmp. 82
Illustrative Examplep. 83
Major advantages and disadvantagesp. 84
Linear Value Function with a Convex Set of Feasible Alternatives: Linear Programmingp. 85
A simple linear program for a technology portfolio decisionp. 85
A general linear program and its basic characteristicsp. 85
Graphical representation of a two-activity linear programp. 86
Graphical solution to a two-activity linear programp. 87
Outline of a systematic solution procedure and the Simplex methodp. 87
Shadow prices of resources and relation to LaGrange multipliersp. 88
Major advantages and disadvantagesp. 89
Efficient Search for a Large Number of Sectionable Alternatives 1: Branch-and-Bound Approachp. 90
Basic algorithmp. 90
Examples of applicationp. 91
Major advantages and applicabilityp. 94
Efficient Search for a Large Number of Sectionable Alternatives 2: Dynamic Programming Approachp. 95
Dynamic programming principle: the principle of optimalityp. 95
Algorithm for allocating M units of resource to n technologiesp. 96
Illustrative examplep. 97
Application to flexible manufacturing plant production mixp. 99
Major advantages and disadvantagesp. 100
Referencesp. 100
Analytic Hierarchy Processp. 100
Generalized LaGrange Multiplier Methodp. 101
Linear Programmingp. 101
Branch-and-Bound Approachp. 101
Dynamic Programmingp. 101
Exercisesp. 101
Find the Optimal Technology Portfolio: Decision Under Uncertaintyp. 103
Decision Tree Analysisp. 103
Decision tree structurep. 103
Analysis procedurep. 105
Single-stage decision tree analysis-breakeven analysisp. 106
Two-stage decision tree analysis-expected value of informationp. 109
Major advantages and disadvantagesp. 111
Portfolio Diversificationp. 112
Portfolio value and riskp. 112
Benefit of diversificationp. 112
Efficient frontier, iso-preference curve, and optimal portfoliop. 115
Major advantages and disadvantagesp. 116
Real Options Theory and Applicationp. 116
Basic concepts of options theoryp. 117
Option valuationp. 118
Major advantages and disadvantagesp. 125
Referencesp. 126
Exercisesp. 128
Monitor Portfolio Progress and Changesp. 131
Project Evaluation and Review Techniquep. 131
Collect data on project activitiesp. 131
Estimate the expected values and variances of individual activity completion timesp. 132
Construct the PERT diagramp. 132
Identify the critical activities, critical path, and expected project completion timep. 133
Estimate variance of project completion time and probability of project completion by a given timep. 134
Develop project budgetingp. 135
Analyze project completion time reduction and extensionp. 136
Use linear programming for project completion time reductionp. 139
Major advantages, limitations, and applicabilityp. 142
Project Portfolio Monitoring System: SRI Early Alert Systemp. 142
Underlying concepts of SEASp. 143
A Simple Illustrative Examplep. 145
Major advantages, limitations, and applicabilityp. 147
Referencesp. 147
Exercisesp. 148
Modify Portoflio to Re-Integrate with Organizational Strategyp. 149
Factor Analysisp. 149
Select and define factorsp. 149
Develop detailed specifications and rating measures of the factorsp. 150
Display assessment of the factors of a technologyp. 151
Conduct an integrated factor analysisp. 151
Strategy Mapp. 153
Develop strategy maps and identify action areasp. 153
Position technologies under different scenariosp. 158
Modify Technology Portfolio to Reintegrate with Organizational Strategyp. 160
Referencesp. 161
Exercisesp. 161
Basic Mathematical, Probability, and Statistical Concepts and Toolsp. 163
Basic Mathematical Concepts and Toolsp. 163
Differentiation and local optimap. 163
Matrix theory and operationsp. 163
Basic Probability Concepts and Toolsp. 164
Probability definitions and rulesp. 164
Probability assignmentp. 164
Bayes Theoremp. 165
Basic Statistical Concepts and Toolsp. 165
Population data and parametersp. 165
Random sample and statisticsp. 166
Central limit theorem, normal and student t distributionsp. 166
Interval estimation and hypothesis testingp. 167
Linear regression analysisp. 167
Indexp. 171
Table of Contents provided by Ingram. All Rights Reserved.

ISBN: 9780387354460
ISBN-10: 0387354468
Series: International Series in Operations Research & Management Science
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 174
Published: 18th December 2006
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 23.5 x 15.6  x 1.27
Weight (kg): 0.99